D<ee>p learning [dev library]

Our project employs machine learning to pinpoint phishing URLs with 97.4% accuracy, leveraging HTTPS and website traffic as critical indicators. Insights into features like AnchorURL enhance cybersecurity strategies, showcasing the power of AI in combating online threats.

Este projeto, desenvolvido durante o curso da Alura, utiliza o algoritmo XGBoost para prever a presença de doenças cardíacas em pacientes com base em um conjunto de dados clínicos. O modelo foi treinado e avaliado utilizando técnicas de validação cruzada e otimização de hiperparâmetros.

This study involves employing machine learning models and anomaly detection approaches, such as over- and under-sampling, to detect fraud in online transactions.

The T20 World Cup Score Prediction project aims to predict the total runs scored by a team in a T20 cricket match using the XGBoost algorithm. XGBoost is a popular machine learning algorithm used for predictive modeling.

This is a end to end Data Science project where the task is to predict the Fare of the flights (Indian Only). Data is in the form of Excel spreadsheets, one is for training purpose and the other is for testing.

Predict future movements from skeleton data. Utilize XGBoost classifier on time series of 3D skeleton data for tasks like fall detection or gesture recognition. Preprocess, train, evaluate, and predict for submission.

This repository presents a comprehensive analysis of bank customer financial product ownership using advanced machine learning techniques. The project leverages a rich dataset containing demographic information, product ownership details, and other relevant attributes such as country of residence, age, and gross income.

XGBoost (Extreme Gradient Boosting) is a highly efficient and accurate machine learning algorithm based on gradient boosting, excelling in structured data tasks. It includes features like regularization, handling missing values, and parallel processing. Widely used in competitions and industry, it supports multiple programming languages.

vitruvius is a wep app manage construction works

A lightweight gradient boosted decision tree package.

Spotify Music Classifier with Machine Learning Using Spotify API

India is one of the countries with the highest air pollution country. Generally, air pollution is assessed by PM value or air quality index value. For my further analysis, I have selected PM-2.5 value to determine the air quality prediction and the India-Bangalore region. Also, the data was collected through web scraping with the help of Beautif…

The study focuses on modeling and predicting H5N1 bird flu outbreaks in the United States at the county level, utilizing diverse statistical techniques and machine learning models.

This project leverages machine learning to forecast currency exchange rates to help optimize expenses in the face of fluctuating currencies.

Used Linear Regression, Decision Tree, Random Forest and XGBoost, AdaBoost, LightGBM and CatBoost ML Algorithm to Predict Bangalore housing price.

Used XGBoost Gradient Boosting Decision Tree Supervised ML Algorithm

In this project i am trying to use NLP, ML concepts on Amazon reviews using various ML based model like XGBoost, Decision tree classifier and random forest

Logical Rhythm is annual Machine learning competition hosted on Kaggle under Avishkar (Official Technical Fest of MNNIT)

Python code for Machine Learning Algorithms